Scientific Knowledge Graphs (SKGs) currently lack systematic approaches for handling geographic data, a particularly relevant limitation in energy planning, where spatial context is crucial for informed decision-making. The SciLake project (Horizon No. 101058573) aims to enhance knowledge discovery by improving the SKG’s infrastructure and services for accessing, integrating, and reusing research data across various disciplines. During the development of the Energy pilot, we created and tested a workflow to systematically detect mentions of geographical entities in scientific texts, analysed their contextual relevance (e.g., study site, case study location, broader regional focus), and mapped these associations on a European scale.
We enriched existing scientific metadata with structured geospatial information using natural language recognition enhanced by AI. We showcase that we can extract geographic mentions of case studies and institutions from open-source research.
The resulting enriched knowledge graph enables researchers, policymakers, and funders to explore research activity through a geographical lens, supporting new forms of discovery, collaboration, and policy analysis. Our work closes the gap between research and practice by providing interactive maps, which are more accessible to broader audiences than API or other current interfaces.
We utilise regional energy planning to demonstrate our approach, which includes addressing challenges related to multiple entity disambiguation. We will discuss how this enrichment pipeline could be integrated into other European Open Science infrastructures. Additionally, we will reflect on broader implications, such as areas lacking research studies, enhancing research discoverability through contextual metadata, and the potential for building more navigable, interoperable, and inclusive open science ecosystems.

This presentation explores a collaborative national network of research data repositories in Poland, where institutional, disciplinary, and generalist infrastructures coexist rather than compete. The model offers a practical example of how interoperability and central coordination can support researchers and institutions in selecting the most appropriate repository type—without duplicating efforts or fragmenting services.

Drawing on a growing ecosystem currently comprising four main repositories (including a generalist platform hosting over 50 institutional dataverses), the presentation demonstrates how this architecture helps address key challenges in the research data landscape:
- ensuring long-term sustainability (technical, operational, and financial),
- alleviating staffing shortages,
- and motivating researchers to share their data.

The model relies on shared infrastructure, harmonized metadata exchange, and cross-repository visibility, enabling researchers to deposit data in the repository best suited to their needs—while benefiting from aggregated institutional presence and increased discoverability.

By presenting this approach, we aim to share insights into a scalable, community-driven strategy that reduces overheads, strengthens national coordination, and enhances the openness of research data practices. By highlighting a collaborative infrastructure model, this presentation contributes to the broader conversation on how we can reimagine openness through shared responsibility, inclusive governance, and sustainable practices.

Open and Commercial: Rethinking Partnerships for Sustainable Open Infrastructure

Can openness and commercial collaboration truly coexist? This panel brings together voices from across sectors to tackle tough questions about trust, funding, and sustainability. Join us for a candid discussion on building equitable, transparent partnerships that support resilient open infrastructure, without compromising core values.

Shaping AI for Open Science: Beyond the Hype

How can AI serve all research communities? This interactive session dives into real-world uses, ethical dilemmas, and collaborative strategies for integrating AI into open science infrastructure. With lightning talks, hands-on mapping, and a lively fishbowl discussion, we will challenge assumptions and co-create a path toward inclusive, responsible AI in research. No tech background needed, just your perspective.

Tracking the Impact of Open Science: Are We Measuring What Matters?

This panel brings together experts to explore how we assess the real-world effects of Open Science. What metrics reflect meaningful change? How can we monitor progress without losing sight of equity and inclusivity? Join us for a lively discussion on tools, frameworks, and lessons shaping the future of Open Science impact and monitoring.

As Open Science accelerates, licensing models must evolve. Join us for a hands-on workshop to explore OpenREL, a new rights expression toolkit developed in Horizon Europe EOSC Beyond project. Learn how to represent complex access and reuse conditions in machine-readable form, from GDPR compliance to dual licensing and ethical constraints. Work through real-life cases with peers, shape the future of rights governance, and help build a FAIRer, trusted Open Science ecosystem.

From Commitment to Action: Making the Barcelona Declaration Work
The Barcelona Declaration on Open Research Information has sparked global momentum, but how do we turn principles into practice? In this collaborative session, we will explore real-world challenges in implementing open research information and co-develop actionable strategies to address them. Whether your organization has signed the Declaration or is just exploring it, join fellow policy makers, open science officers, and infrastructure providers to help shape a shared roadmap for openness, equity, and responsible research assessment.

In this talk we propose to survey the computational reproducibility practices, opportunities and challenges in view of fostering Open and FAIR Science in research communities.

We discuss several thinking models regarding computational reproducibility, focusing on the broader knowledge preservation and reuse aspects rather than on the raw computing evolution aspects.

Building upon several use cases from experimental particle physics and related scientific disciplines, we discuss the variety of sociological and technological challenges inherent in making the research innately reproducible and reusable.

From the researcher point of view, we argue how "preproducibility" should come early in the scientific process in order to ensure its future reusability.

From the data infrastructure point of view, we argue how the data repository services benefit from accompanying "analysis engines" to ensure the correctness of data curation procedures of the validity of data usage recipes.

The ultimate goal of the Open Science and Data Preservation efforts is to facilitate future reuse and reinterpretation of scientific data by new generation of researchers. A strong focus on the computational reproducibility of original data analyses provides a way to facilitate the reuse and reinterpretation of Open and FAIR data even many years after the original publication.

This talk is heavily inspired, but not limited to, the experiences and lessons learnt from the past ten years of running the CERN Open Data portal and the REANA reproducible analysis platform for the particle physics community.

The initiative of the European Research Area (ERA) aims at creating a unified research and innovation space across Europe. One of the key objectives of ERA is to promote open access to research results and data, thus encouraging transparency, reproducibility, and wider dissemination of knowledge. In order to achieve an alignment with this ERA objective (and others), the European Research Area National Action Plan (ERA-NAP) supports the individual EU member states to contribute to a European Open Science infrastructure.

In this way, national measures for an open science infrastructure are promoted, which ultimately aim to create an open science infrastructure within a European framework. Open Science policies are the means of choice for the creation of such a structure at national level – because only they guarantee the joint endeavour to bundle the interests and needs of all stakeholders.

In my presentation, I outline the goals and challenges of working on such a national Open Science policy using the example of research data management in the Austrian Higher Education Area, which a working group of the Austrian University Conference has addressed, in line with the ERA-NAP. How do different types of universities define research data? What restrictions regarding openness do they wish to reserve for themselves - and for what reasons? Up to what point can a framework policy form a common ground – and at what point should individual standards be applied?

The EU-funded OSTrails project is building a federated Open Science infrastructure by enabling researchers and institutions to discover, plan, track, and assess their work in transparent and interoperable ways. With 41 partners and 25 pilots—including cross-domain, national, and Horizon Europe testbeds—OSTrails is piloting the practical integration of over 80 interoperable tools and services. This diversity reflects the scale needed to support a truly federated Open Science ecosystem.

At the core of the project are two key enablers: a modular Interoperability Reference Architecture and a tool independent Plan-Track-Assess (PTA) framework. Together, these provide a shared foundation for aligning diverse research management services—from Data Management Planning platforms to Scientific Knowledge Graphs and FAIR assessment tools—across distributed infrastructures.

To ensure long-term impact, OSTrails has launched a comprehensive training and capacity-building programme, equipping research communities and service providers with the knowledge and tools to adopt and extend project outcomes. These efforts build on the co-designed pilots, which validate interoperability across varied institutional, disciplinary settings.

For researchers, OSTrails simplifies cross-institutional Research Data Management workflows and clarifies pathways to Open Science best practices. For service providers, it offers a practical model for aligning with EOSC while retaining domain-specific autonomy.

This presentation will showcase how OSTrails contributes to a federated EOSC ecosystem by delivering standards-driven solutions that prioritise interoperability and FAIRness as essential components of a sustainable and inclusive infrastructure, supporting both federation and the development of the Web of FAIR Data and Services.

Repositories at the Heart of Open Science and AI Innovation

Open Science needs trusted, visible, and inclusive research outputs—and repositories are key. This panel showcases the IMPACT-REPO Action Plan and highlights innovative repository services that boost research impact, build trust, and support AI-driven discovery. Join us to explore how Europe’s repositories are evolving from access points to strategic engines of open science.

Open Science infrastructures have significantly advanced global knowledge sharing, enabling wider access, collaboration, and transparency in research. However, alongside these achievements, we face substantial challenges from spam and malicious activities that threaten the integrity of scholarly communications and pollute the scholarly graph. These challenges include the exponential growth of AI-generated content that blurs the line between legitimate research and sophisticated fabrication, rampant plagiarism facilitated by easily accessible digital content, and predatory journals that exploit the openness of publication channels for commercial gain.

Further, covert and aggressive data harvesting practices threaten to take down repositories, while the dual-use nature of open platforms can inadvertently facilitate unethical uses of openly shared research. Addressing these challenges demands rigorous governance, novel technical implementations such as advanced machine-learning classifiers to detect spam, and coordinated community-driven moderation policies.

In this session, we explore practical experiences and innovative solutions from managing Zenodo, a large-scale open science infrastructures, focusing on balancing openness with robust security measures. We discuss emerging practices to mitigate risks, enhance metadata quality, and uphold the credibility and fairness of open science systems. The presentation aims to engage the community in a critical discussion about proactive strategies and collaborative approaches to safeguard open science from exploitation.